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Downtime Costs Global 2000 Companies $400 Billion Annually

The total cost of downtime for Global 2000 companies is $400 billion annually — or 9% of profits — when digital environments fail unexpectedly, according to The Hidden Costs of Downtime, a new report from Splunk, in collaboration with Oxford Economics.


Source: Splunk

The analysis revealed the consequences of downtime go beyond immediate financial costs and take a lasting toll on a company's shareholder value, brand reputation, innovation velocity and customer trust.

Unplanned downtime — any service degradation or outage of a business system — can range from a frustrating inconvenience to a life-threatening scenario for customers. The report surveyed 2,000 executives from the largest companies worldwide (Global 2000) and showed downtime causes both direct and hidden costs as defined below:

Direct costs are clear and measurable to a company. Examples of direct costs are lost revenue, regulatory fines, missed SLA penalties and overtime wages.

Hidden costs are harder to measure and take longer to have an impact, but can be just as detrimental. Examples of hidden costs include diminished shareholder value, stagnant developer productivity, delayed time-to-market, tarnished brand reputation and more.

The report also highlighted the origins of downtime — 56% of downtime incidents are due to security incidents such as phishing attacks, while 44% stem from application or infrastructure issues like software failures. Human error is the number one cause of downtime and the biggest offender for both scenarios.

However, there are practices that can help reduce downtime occurrences and lessen the impacts of direct and hidden costs. The research revealed an elite group of companies — the top 10% — are more resilient than the majority of respondents, suffering less downtime, having lower total direct costs and experiencing minimal impacts from hidden costs. The report calls these organizations "resilience leaders" and their shared strategies and traits provide a blueprint for bouncing back faster. Resilience leaders were calculated based on frequency of downtime and amount of economic damage experienced from hidden costs. Resilience leaders are also more mature in their adoption of generative AI, expanding their use of embedded generative AI features in existing tools at four times the rate of other organizations.

The Combined Direct and Hidden Costs

The repercussions of downtime are not limited to a single department or cost category. The report surveyed Chief Financial Officers (CFOs) and Chief Marketing Officers (CMOs), as well as security, ITOps and engineering professionals to quantify the cost of downtime across several dimensions.

Key findings on the impacts of downtime include:

Revenue loss is the number one cost. Due to downtime, lost revenue was calculated as $49M annually, and it can take 75 days for that revenue to recover. The second largest cost is regulatory fines, averaging at $22M per year. Missed SLA penalties come in third at $16M.

Diminishes shareholder value. Organizations can expect their stock price to drop by as much as 9% after a single incident, and on average, it takes an average of 79 days to recover.

Drains budgets due to cyberattacks. When experiencing a ransomware attack, 67% of surveyed CFOs advised their CEO and board of directors to pay up, either directly to the perpetrator, through insurance, a third party or all three. The combination of ransomware and extortion payouts cost $19M annually.

Curbs innovation velocity. 74% of technology executives surveyed experienced delayed time-to-market, and 64% experienced stagnant developer productivity, as a result of downtime. Any service degradation often results in teams shifting from high-value work to applying software patches and participating in postmortems.

Sinks lifetime value and customer confidence. Downtime can dilute customer loyalty and damage public perception. 41% of tech executives in the report admit customers are often or always the first to detect downtime. In addition, 40% of Chief Marketing Officers (CMOs) reveal that downtime impacts customer lifetime value (CLV), and another 40% say it damages reseller and/or partner relationships.

Globally, the average cost of downtime per year is more costly for US companies ($256M) than their global counterparts due to various factors including regulatory policies and digital infrastructure. The cost of downtime in Europe reaches $198M, and $187M in the Asia-Pacific region (APAC). Organizations in Europe — where workforce oversight and cyber regulation are stricter — pay more in overtime wages ($12M) and to recover from backups ($9M). Geography also shapes how quickly an organization recovers financially post-incident. Europe and APAC hold the longest recovery times, while companies in Africa and the Middle East recover the fastest.

"Disruption in business is unavoidable. When digital systems fail unexpectedly, companies not only lose substantial revenue and risk facing regulatory fines, they also lose customer trust and reputation," said Gary Steele, President of Go-to-Market, Cisco & GM, Splunk. "How an organization reacts, adapts and evolves to disruption is what sets it apart as a leader. A foundational building block for a resilient enterprise is a unified approach to security and observability to quickly detect and fix problems across their entire digital footprint."

Resilience Leaders Bounce Back Faster

Resilience leaders, or companies that recover faster from downtime, share common traits and strategies that provide a blueprint for digital resilience. They also invest more strategically, rather than simply investing more. The resilience leaders' common strategies and traits include:

Investing in both security and observability. Compared to other respondents, resilience leaders spend $12M more on cybersecurity tools and $2.4M more on observability tools.

Embracing the benefits of GenAI. Resilience leaders are also more mature in their adoption of generative AI, expanding their use of embedded generative AI features in existing tools at four times the rate, compared to the remaining respondents.

Recovering more quickly. Faster recovery often equates to a better customer experience and less unwanted media attention. Resilience leaders' mean time to recover (MTTR) from application or infrastructure-related downtime is 28% faster than the majority of respondents, and 23% faster from cybersecurity-related incidents.

Experiencing less toll from hidden costs. Most resilience leaders experience no damage from hidden costs, or describe it as "moderate." That is in stark contrast with the remaining 90% of organizations that call hidden cost impacts "moderately" or "very" damaging.

Dodging financial damage. Resilience leaders reduce revenue loss by $17M, lower the financial impact of regulatory fines by $10M and cut down ransomware payouts by $7M.

Methodology: Oxford Economics researchers surveyed 2,000 executives from Forbes' Global 2000 companies in technology (including security, IT and engineering titles), finance (including Chief Financial Officers) and marketing functions (including Chief Marketing Officers.) The report surveyed 53 countries, in regions including Africa, APAC, Europe, the Middle East, North America and South America. In addition, respondents were from 10 industries: energy and utilities, financial services, healthcare and life sciences, information services and technology, manufacturing, communications and media, public sector, retail, transportation and logistics and travel and hospitality.

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Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

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Downtime Costs Global 2000 Companies $400 Billion Annually

The total cost of downtime for Global 2000 companies is $400 billion annually — or 9% of profits — when digital environments fail unexpectedly, according to The Hidden Costs of Downtime, a new report from Splunk, in collaboration with Oxford Economics.


Source: Splunk

The analysis revealed the consequences of downtime go beyond immediate financial costs and take a lasting toll on a company's shareholder value, brand reputation, innovation velocity and customer trust.

Unplanned downtime — any service degradation or outage of a business system — can range from a frustrating inconvenience to a life-threatening scenario for customers. The report surveyed 2,000 executives from the largest companies worldwide (Global 2000) and showed downtime causes both direct and hidden costs as defined below:

Direct costs are clear and measurable to a company. Examples of direct costs are lost revenue, regulatory fines, missed SLA penalties and overtime wages.

Hidden costs are harder to measure and take longer to have an impact, but can be just as detrimental. Examples of hidden costs include diminished shareholder value, stagnant developer productivity, delayed time-to-market, tarnished brand reputation and more.

The report also highlighted the origins of downtime — 56% of downtime incidents are due to security incidents such as phishing attacks, while 44% stem from application or infrastructure issues like software failures. Human error is the number one cause of downtime and the biggest offender for both scenarios.

However, there are practices that can help reduce downtime occurrences and lessen the impacts of direct and hidden costs. The research revealed an elite group of companies — the top 10% — are more resilient than the majority of respondents, suffering less downtime, having lower total direct costs and experiencing minimal impacts from hidden costs. The report calls these organizations "resilience leaders" and their shared strategies and traits provide a blueprint for bouncing back faster. Resilience leaders were calculated based on frequency of downtime and amount of economic damage experienced from hidden costs. Resilience leaders are also more mature in their adoption of generative AI, expanding their use of embedded generative AI features in existing tools at four times the rate of other organizations.

The Combined Direct and Hidden Costs

The repercussions of downtime are not limited to a single department or cost category. The report surveyed Chief Financial Officers (CFOs) and Chief Marketing Officers (CMOs), as well as security, ITOps and engineering professionals to quantify the cost of downtime across several dimensions.

Key findings on the impacts of downtime include:

Revenue loss is the number one cost. Due to downtime, lost revenue was calculated as $49M annually, and it can take 75 days for that revenue to recover. The second largest cost is regulatory fines, averaging at $22M per year. Missed SLA penalties come in third at $16M.

Diminishes shareholder value. Organizations can expect their stock price to drop by as much as 9% after a single incident, and on average, it takes an average of 79 days to recover.

Drains budgets due to cyberattacks. When experiencing a ransomware attack, 67% of surveyed CFOs advised their CEO and board of directors to pay up, either directly to the perpetrator, through insurance, a third party or all three. The combination of ransomware and extortion payouts cost $19M annually.

Curbs innovation velocity. 74% of technology executives surveyed experienced delayed time-to-market, and 64% experienced stagnant developer productivity, as a result of downtime. Any service degradation often results in teams shifting from high-value work to applying software patches and participating in postmortems.

Sinks lifetime value and customer confidence. Downtime can dilute customer loyalty and damage public perception. 41% of tech executives in the report admit customers are often or always the first to detect downtime. In addition, 40% of Chief Marketing Officers (CMOs) reveal that downtime impacts customer lifetime value (CLV), and another 40% say it damages reseller and/or partner relationships.

Globally, the average cost of downtime per year is more costly for US companies ($256M) than their global counterparts due to various factors including regulatory policies and digital infrastructure. The cost of downtime in Europe reaches $198M, and $187M in the Asia-Pacific region (APAC). Organizations in Europe — where workforce oversight and cyber regulation are stricter — pay more in overtime wages ($12M) and to recover from backups ($9M). Geography also shapes how quickly an organization recovers financially post-incident. Europe and APAC hold the longest recovery times, while companies in Africa and the Middle East recover the fastest.

"Disruption in business is unavoidable. When digital systems fail unexpectedly, companies not only lose substantial revenue and risk facing regulatory fines, they also lose customer trust and reputation," said Gary Steele, President of Go-to-Market, Cisco & GM, Splunk. "How an organization reacts, adapts and evolves to disruption is what sets it apart as a leader. A foundational building block for a resilient enterprise is a unified approach to security and observability to quickly detect and fix problems across their entire digital footprint."

Resilience Leaders Bounce Back Faster

Resilience leaders, or companies that recover faster from downtime, share common traits and strategies that provide a blueprint for digital resilience. They also invest more strategically, rather than simply investing more. The resilience leaders' common strategies and traits include:

Investing in both security and observability. Compared to other respondents, resilience leaders spend $12M more on cybersecurity tools and $2.4M more on observability tools.

Embracing the benefits of GenAI. Resilience leaders are also more mature in their adoption of generative AI, expanding their use of embedded generative AI features in existing tools at four times the rate, compared to the remaining respondents.

Recovering more quickly. Faster recovery often equates to a better customer experience and less unwanted media attention. Resilience leaders' mean time to recover (MTTR) from application or infrastructure-related downtime is 28% faster than the majority of respondents, and 23% faster from cybersecurity-related incidents.

Experiencing less toll from hidden costs. Most resilience leaders experience no damage from hidden costs, or describe it as "moderate." That is in stark contrast with the remaining 90% of organizations that call hidden cost impacts "moderately" or "very" damaging.

Dodging financial damage. Resilience leaders reduce revenue loss by $17M, lower the financial impact of regulatory fines by $10M and cut down ransomware payouts by $7M.

Methodology: Oxford Economics researchers surveyed 2,000 executives from Forbes' Global 2000 companies in technology (including security, IT and engineering titles), finance (including Chief Financial Officers) and marketing functions (including Chief Marketing Officers.) The report surveyed 53 countries, in regions including Africa, APAC, Europe, the Middle East, North America and South America. In addition, respondents were from 10 industries: energy and utilities, financial services, healthcare and life sciences, information services and technology, manufacturing, communications and media, public sector, retail, transportation and logistics and travel and hospitality.

Hot Topics

The Latest

Like most digital transformation shifts, organizations often prioritize productivity and leave security and observability to keep pace. This usually translates to both the mass implementation of new technology and fragmented monitoring and observability (M&O) tooling. In the era of AI and varied cloud architecture, a disparate observability function can be dangerous. IT teams will lack a complete picture of their IT environment, making it harder to diagnose issues while slowing down mean time to resolve (MTTR). In fact, according to recent data from the SolarWinds State of Monitoring & Observability Report, 77% of IT personnel said the lack of visibility across their on-prem and cloud architecture was an issue ...

In MEAN TIME TO INSIGHT Episode 23, Shamus McGillicuddy, VP of Research, Network Infrastructure and Operations, at EMA discusses the NetOps labor shortage ... 

Technology management is evolving, and in turn, so is the scope of FinOps. The FinOps Foundation recently updated their mission statement from "advancing the people who manage the value of cloud" to "advancing the people who manage the value of technology." This seemingly small change solidifies a larger evolution: FinOps practitioners have organically expanded to be focused on more than just cloud cost optimization. Today, FinOps teams are largely — and quickly — expanding their job descriptions, evolving into a critical function for managing the full value of technology ...

Enterprises are under pressure to scale AI quickly. Yet despite considerable investment, adoption continues to stall. One of the most overlooked reasons is vendor sprawl ... In reality, no organization deliberately sets out to create sprawling vendor ecosystems. More often, complexity accumulates over time through well-intentioned initiatives, such as enterprise-wide digital transformation efforts, point solutions, or decentralized sourcing strategies ...

Nearly every conversation about AI eventually circles back to compute. GPUs dominate the headlines while cloud platforms compete for workloads and model benchmarks drive investment decisions. But underneath that noise, a quieter infrastructure challenge is taking shape. The real bottleneck in enterprise AI is not processing power, it is the ability to store, manage and retrieve the relentless volumes of data that AI systems generate, consume and multiply ...

The 2026 Observability Survey from Grafana Labs paints a vivid picture of an industry maturing fast, where AI is welcomed with careful conditions, SaaS economics are reshaping spending decisions, complexity remains a defining challenge, and open standards continue to underpin it all ...

The observability industry has an evolving relationship with AI. We're not skeptics, but it's clear that trust in AI must be earned ... In Grafana Labs' annual Observability Survey, 92% said they see real value in AI surfacing anomalies before they cause downtime. Another 91% endorsed AI for forecasting and root cause analysis. So while the demand is there, customers need it to be trustworthy, as the survey also found that the practitioners most enthusiastic about AI are also the most insistent on explainability ...

In the modern enterprise, the conversation around AI has moved past skepticism toward a stage of active adoption. According to our 2026 State of IT Trends Report: The Human Side of Autonomous AI, nearly 90% of IT professionals view AI as a net positive, and this optimism is well-founded. We are seeing agentic AI move beyond simple automation to actively streamlining complex data insights and eliminating the manual toil that has long hindered innovation. However, as we integrate these autonomous agents into our ecosystems, the fundamental DNA of the IT role is evolving ...

AI workloads require an enormous amount of computing power ... What's also becoming abundantly clear is just how quickly AI's computing needs are leading to enterprise systems failure. According to Cockroach Labs' State of AI Infrastructure 2026 report, enterprise systems are much closer to failure than their organizations realize. The report ... suggests AI scale could cause widespread failures in as little as one year — making it a clear risk for business performance and reliability.

The quietest week your engineering team has ever had might also be its best. No alarms going off. No escalations. No frantic Teams or Slack threads at 2 a.m. Everything humming along exactly as it should. And somewhere in a leadership meeting, someone looks at the metrics dashboard, sees a flat line of incidents and says: "Seems like things are pretty calm over there. Do we really need all those people?" ... I've spent many years in engineering, and this pattern keeps repeating ...